Reciprocity in international interuniversity global health partnerships
Bibliographic record
Abstract
Interuniversity global health partnerships are often between parties unequal in organizational capacity and performance using conventional academic output measures. Mutual benefit and reciprocity are called for but literature examining these concepts is limited. The objectives of this study are to analyse how reciprocity is practiced in international interuniversity global health partnerships and to identify relevant structures of reciprocity. Four East African universities and 125 of their international partnerships were included. A total of 192 representatives participated in key informant interviews and focus group discussions. Interviews were transcribed and analysed thematically, drawing on reciprocity theories from international relations and sociology. A range of reciprocal exchanges, including specific, unilateral and diffuse (bilateral and multilateral), were observed. Many partnerships violated the principle of equivalence, as exchanges were often not equal based on tangible benefits realized. Only when intangible benefits, like values, were considered was equivalence realized. This changed the way the principle of contingency—an action done for benefit received—was observed within the partnerships. The values of individuals, the structures of organizations and the guiding principles of the partnerships were observed to guide more than financial gain. Asymmetry of partners, dissimilar perspectives and priorities, and terms of funding all pose challenges to reciprocity. In an era when strengthening institutions is considered crucial to achieving development goals, more rigorous examination and assessment of reciprocity in partnerships is warranted.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.039 | 0.068 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".